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Chapter 6. Relevance and Ranking

You’re now armed with a good chunk of knowledge about getting up and
running with Sphinx, creating and managing indexes, and writing proper
queries. However, there’s one more skill that’s of use with nearly every
site: improving search quality. So, let’s spend some time discussing quality
in general and what Sphinx can offer, shall we?

Relevance Assessment: A Black Art

We can’t really chase down “search quality” until we formally define
it and decide how we measure it. An empirical approach, as in “Here, I
just made up another custom ranking rule out of thin air and I think it
will generally improve our results any time of day,” wears out very soon.
After about the third such rule, you can no longer manage such an
approach, because the total number of rule combinations explodes combinatorially, and arguing about (not to
mention proving) the value of every single combination quickly becomes
impossible. A scientific approach, as in “Let us introduce some
comprehensible numerical metrics that can be computed programmatically and
then grasped intuitively,” yields to automation and scales somewhat
better.

So, what is search quality? Chapter 1 mentioned that documents in the
result set are, by default, ordered using a relevance
ranking function that assigns a different weight to every document, based on the current query, document contents, other document attributes, and other factors. But it’s very important to realize that the relevance value that is computed ...

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